Digital & Technology Compliance
AI Governance & Validation
Independent AI risk assessments, validation strategy, governance framework design and AI supplier qualification for pharmaceutical, biotechnology and medical device organisations operating in GxP environments.
Executive Overview
Artificial intelligence is entering pharmaceutical manufacturing, quality control and regulatory affairs at pace. Predictive quality models, automated deviation detection, AI-assisted literature review, generative AI for documentation and machine learning in process analytical technology are no longer theoretical applications — they are being deployed across regulated operations globally. What has not kept pace is the governance infrastructure required to make these deployments defensible to regulators.
EU GMP Annex 22, published in 2023, establishes specific expectations for the governance, validation and ongoing monitoring of AI systems used in GMP-regulated activities. The FDA has issued AI/ML guidance applicable to software as a medical device and broader manufacturing contexts. Regulators on both sides of the Atlantic are beginning to inspect AI governance as a standalone subject, with organisations expected to demonstrate that AI systems are controlled, validated and overseen with the same rigour as any other GxP system.
Sthira Assure provides independent AI governance assessments, validation strategy development and AI supplier qualification services grounded in current regulatory expectations. We work with organisations at every stage of AI adoption — from those designing governance frameworks before first deployment through to those responding to inspection observations about existing AI use.
Regulatory Frameworks
- EU GMP Annex 22
- FDA AI/ML Action Plan
- EMA Reflection Paper on AI
- ISO 13485 (Medical Devices)
- ISPE GAMP AI SIG Guidance
- ICH Q9 (Risk Management)
- EU AI Act
Discuss AI Governance
Speak with our team about your AI systems and regulatory obligations.
Request a ConsultationCommon Compliance Risks
Absence of AI Governance Frameworks
Most regulated organisations are adopting AI tools without established governance structures. Without defined roles, risk classification procedures and oversight mechanisms, AI use in GxP processes cannot be systematically controlled. Regulators expect governance frameworks before AI is deployed in quality-critical applications — not after.
Inadequate Validation of AI Systems
Traditional computer system validation approaches do not adequately address AI and machine learning systems, which exhibit non-deterministic behaviour and evolve over time. EU GMP Annex 22 and emerging FDA guidance require risk-based validation strategies that address model explainability, bias, drift and ongoing monitoring, areas that conventional CSV protocols do not cover.
AI Supplier Qualification Gaps
AI tools procured from commercial vendors introduce new qualification obligations. Organisations must assess not only the vendor's quality system but also the data used to train the model, the model validation evidence provided and the change notification commitments for model updates. Most existing supplier qualification programmes do not address these requirements.
Audit Trail and Explainability Obligations
Regulatory authorities expect that decisions made using AI systems in GxP contexts can be reviewed, justified and reproduced. AI systems that operate as black boxes, without interpretable decision pathways or comprehensive audit trails, present both regulatory and product quality risks. This is particularly acute for AI used in batch release, laboratory analysis and complaint handling.
Scope of Services
Our AI governance services address the full lifecycle of AI system management in regulated environments — from initial risk assessment and governance framework design through to validation, supplier qualification and ongoing monitoring.
Typical Deliverables
Our AI governance engagements produce documented outputs that directly support your regulatory submissions, quality system records and inspection responses.
Frequently Asked Questions
Which regulations govern AI use in pharmaceutical manufacturing?
EU GMP Annex 22 (Computerised Systems — Use of Artificial Intelligence) is the primary EU framework, published in 2023. The FDA has issued AI/ML-based Software as a Medical Device guidance and a broader AI action plan. The EMA has published reflection papers on the use of AI in medicines development and manufacturing. ISPE also provides supplementary guidance through its GAMP AI Special Interest Group.
Does Annex 22 apply to all AI systems in pharma?
EU GMP Annex 22 applies to AI systems used in GMP-regulated activities, including manufacturing, quality control, quality assurance and distribution. AI systems used purely for business administration or non-GxP purposes fall outside its scope. Risk classification of AI systems based on their GxP impact is the starting point for determining applicable requirements.
What is the difference between AI validation and traditional CSV?
Traditional computer system validation addresses deterministic software behaviour against fixed specifications. AI systems, particularly machine learning models, are non-deterministic and can change behaviour as they learn from new data. AI validation must address training data quality, model performance metrics, explainability, monitoring for drift and a defined process for managing model updates — none of which are covered in standard CSV frameworks.
How do you assess generative AI tools used in regulated environments?
We assess generative AI tools against the risk profile of their specific application. Key areas include data provenance and training data quality, output reliability and hallucination risk, audit trail completeness, supplier validation evidence and change control commitments. We also assess how the tool integrates with existing GxP systems and what oversight mechanisms are in place for AI-generated outputs.
Discuss Your AI Governance Needs
Contact our team to discuss your AI systems, applicable regulatory framework and the governance programme your organisation requires.